Evidence map›Paper›PMID 40548087›Full record

ArticleApplied biosafety : journal of the American Biological Safety Association2025

A Case Study of Biosafety Considerations and Solutions for Work with Highly Pathogenic Avian Influenza Virus with Large-Scale Equipment in High Biocontainment.

Nicholas J Chaplinski, Nancy Mead, David Haley, Erica Spackman

Abstract read
In one paragraph

Article in Applied biosafety : journal of the American Biological Safety Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nicholas J ChaplinskiUSDA-ARS (Agricultural Research Service), U.S. National Poultry Research Center, Athens, Georgia, USA.
Nancy MeadUSDA-ARS (Agricultural Research Service), U.S. National Poultry Research Center, Athens, Georgia, USA.
David HaleyUSDA-ARS (Agricultural Research Service), U.S. National Poultry Research Center, Athens, Georgia, USA.
Erica SpackmanExotic and Emerging Avian Viral Diseases Unit, USDA-ARS (Agricultural Research Service), U.S. National Poultry Research Center, Athens, Georgia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Highly pathogenic avian influenza virus (HPAIV), a potential pandemic pathogen (PPP), was discovered in a new species, cattle, in March 2024 in the United States. Soon thereafter it was discovered that infectious virus could be present in milk at very high titers (up to 10 log Methods: Numerous information sources, including subject matter experts, were utilized to acquire information for risk assessments and to develop procedures for a new, large-scale piece of equipment that required 5L of a PPP at a high titer per test. Results: Application-specific equipment such as sample and waste vessels with sealed ports, tubing with valved connection, and high efficiency particulate air-filtered vents were designed with corresponding safety procedures, such as seal integrity testing of the sample vessels. Conclusions: The use of high volumes of infectious material, the scale of the equipment, and time constraints presented unique challenges to balance biosafety and research objectives. Innovative engineering and procedural approaches allowed the research to be completed successfully in a time-sensitive manner while mitigating biosafety risk.

Indexed as

ABSL-3Aghigh-containment biorisk managementhighly pathogenic avian influenza virusinfluenza biosafetylarge-scale equipment biosafety

Identifiers

PMID40548087
PMCPMC12179349

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.